On Thu, Jul 19, 2012 at 12:42:25AM +0200, federico vaggi wrote:
> I was looking for suggestions for a good ML textbook - ideally one that has
> a heavy emphasis on applications and is based on Python.
I don't know personally any that is based on Python. My favorite machine
learning book is 'The El
On Wed, Jul 18, 2012 at 05:50:16PM -0400, Zach Bastick wrote:
> But this doesn't:
> clf.fit([[0, 0, 0], [1, 1, 1]], [0, 1])
Works for me.
I don't understand what excatly is your problem.
Gael
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Live Security Virtual Co
Hello everyone,
I have a custom prediction class which in fact consists of a random forest
regressor+classifier. The class implements a fit() method, which in turn
calls the fit() methods of the classifier and regressor. Here is the code
for my class: http://paste.org/51862
When i use the class a
Hi everyone,
I was looking for suggestions for a good ML textbook - ideally one that has
a heavy emphasis on applications and is based on Python. I have heard
mixed reviews of:
http://www.amazon.com/Machine-Learning-Algorithmic-Perspective-Recognition/dp/1420067184
and
I was told that for pure th
Jake,
I'm using 0.11
Another example is that this works:
clf.fit([[0, 0], [1, 1]], [0, 1])
But this doesn't:
clf.fit([[0, 0, 0], [1, 1, 1]], [0, 1])
I'm not sure whether this is related, but I installed Pyth yesterday..
http://pypi.python.org/pypi/pyth/
Zach
On 18/07/2012 17:41, Jake Vanderpl
Zach,
For your second snippet, I get this output using the dev version of
scikit-learn:
coef array [ 0. 0. 0.]
length 3
getting value 0: 0.
getting value 1: 0.
What version of scikit-learn are you using? You can find out by runni
I'm having trouble with linear_model.LinearRegression()
This works:
from sklearn import linear_model
clf = linear_model.LinearRegression()
clf.fit ([[0, 0, 0], [1, 1, 1], [2, 2, 2]], [0, 1, 2])
# clf.fit([[394, 3878, 13, 4, 0, 0],[384, 10175, 14, 4, 0, 0]],[3,9])
print 'coef array',clf.coef_
prin
That worked! I had a relatively clean install so removing did not cause damage.
Thanks
On Thu, Jul 19, 2012 at 3:16 AM, Jake Vanderplas
wrote:
> Hi David,
> This sort of error generally is due to having multiple copies of numpy
> on your system. One is being used during compilation, and anothe
On Wed, Jul 18, 2012 at 12:16:57PM -0700, Jake Vanderplas wrote:
>apt-get uninstall python-numpy python-scipy
> and then install numpy and scipy through easy_install.
You probably cannot realistically do that, as numpy is used by fairly
core libraries of the system (python-gtk for instance, I
Hi David,
This sort of error generally is due to having multiple copies of numpy
on your system. One is being used during compilation, and another
incompatible one is being used by your python interpreter.
I would do
apt-get uninstall python-numpy python-scipy
and then install numpy and scipy
Hi,
I am on ubuntu 10.04
I installed
apt-get install python-numpy python-scipy
easy_install scikit-learn
When I import the followig, I get the below error. How do I resolve?
from sklearn import svm
Python 2.6.5 (r265:79063, Apr 16 2010, 13:57:41)
[GCC 4.4.3] on linux2
Type "help", "copyright
2012/7/18 Peter Prettenhofer :
> 2012/7/18 Philipp Singer :
>> Yes, I am currently trying around with tf only, but the vocabulary is
>> still dependen on the corpus.
>
> I would fit the vectorizor on both datasets (such that the vocabulary
> covers the union) and then fit the IDF transformers on ea
2012/7/18 Philipp Singer :
> Am 18.07.2012 15:32, schrieb Peter Prettenhofer:
In this case I would fit one MultinomialNB for the foreground model and
one for the background model. But how would I do the feature extraction
(I have text documents) in this case? Would I fit (e.g., tfidf
Am 18.07.2012 15:32, schrieb Peter Prettenhofer:
>>> In this case I would fit one MultinomialNB for the foreground model and
>>> one for the background model. But how would I do the feature extraction
>>> (I have text documents) in this case? Would I fit (e.g., tfidf) on the
>>> whole corpus (foreg
>> In this case I would fit one MultinomialNB for the foreground model and
>> one for the background model. But how would I do the feature extraction
>> (I have text documents) in this case? Would I fit (e.g., tfidf) on the
>> whole corpus (foreground + background) and then transform both datasets
2012/7/18 Philipp Singer :
> Am 09.07.2012 14:44, schrieb Peter Prettenhofer:
>> 2012/7/9 Philipp Singer :
>>> Am 09.07.2012 13:47, schrieb Peter Prettenhofer:
Hi,
>>>
>>> Hey!
some quick thoughts:
- if you use a multinomial Naive Bayes classifier (aka a language
model
Am 09.07.2012 14:44, schrieb Peter Prettenhofer:
> 2012/7/9 Philipp Singer :
>> Am 09.07.2012 13:47, schrieb Peter Prettenhofer:
>>> Hi,
>>
>> Hey!
>>>
>>> some quick thoughts:
>>>
>>> - if you use a multinomial Naive Bayes classifier (aka a language
>>> model) you can fit a background model on the
2012/7/17 Rafael Almeida :
> Hello,
>
> I'm experimenting with k-means clustering. When using certain values for k,
> silhouette score returns NaN. Is that a bug or is that how it's supposed to
> work? What does it mean? If it is not a bug, I think the function should
> return something more meanin
Hello,
I'm experimenting with k-means clustering. When using certain values for k,
silhouette score returns NaN. Is that a bug or is that how it's supposed to
work? What does it mean? If it is not a bug, I think the function should return
something more meaningful when it fails.
[]'s
Rafael---
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